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Data Modeling for the Business
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About the Author

Steve Hoberman balances the formality and precision of data modeling with the realities of building software systems with severe time, budget, and people constraints. In his consulting and teaching, he focuses on templates, tools, and guidelines to reap the benefits of data modeling with minimal investment. He taught his first data modeling class in 1992 and has educated more than 10,000 people about data modeling and business intelligence techniques since then, spanning every continent except Africa and Antarctica. Steve is the author of seven books on data modeling, including the bestseller Data Modeling Made Simple. He is the founder of the Design Challenges group, inventor of the Data Model Scorecard(R), Conference Chair of the Data Modeling Zone conference, recipient of the 2012 Data Administration Management Association (DAMA) International Professional Achievement Award, and highest rated presenter at Enterprise Data World 2014. Steve can be reached at me@stevehoberman.com, @DataMdlRockStar on Twitter, or through Steve Hoberman on Linked-In. Donna Burbank has a unique perspective on the field of data modelling -- having helped to design and produce several of the leading metadata and data modelling tools in the market today, as well as having spent many years as a consultant implementing these solutions. As a consultant, she has worked with Global 2000 companies world-wide and as a software provider, she has been instrumental in the development efforts at Platinum Technology, Embarcadero Technologies, and CA. Christopher Bradley has spent almost 30 years in the field of Information Management working on Master Data Management, Enterprise Architecture, Metadata Management, Data Warehouse and Business Intelligence implementations. Currently, Chris heads the Business Consultancy practice at IPL, a UK-based consultancy.

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Watch the author describe this informative book in this short video. Learn about the High-Level Data Model and master the techniques for building one, including a comprehensive ten-step approach and hands-on exercises to help you practice topics on your own. In this book, we review data modeling basics and explain why the core concepts stored in a high-level data model can have significant business impact on an organization. We explain the technical notation used for a data model and walk through some simple examples of building a high-level data model. We also describe how data models relate to other key initiatives you may have heard of or may be implementing in your organization.

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